A Study of Tool Planning for FRT-PLR-L/R Stamping Process by using Forming Analysis

2008 ◽  
Vol 32 (10) ◽  
pp. 890-896 ◽  
Author(s):  
Dong-Won Jung ◽  
Dae-Lim Ko
Keyword(s):  
Stamping Process ◽  
Forming Analysis ◽  
Tool Planning

A Study of Selecting Material for Forming Analysis in Auto-Body Panel Stamping Process

2005 ◽  
Vol 29 (3) ◽  
pp. 484-494
Author(s):  
Jae Sin Hwang ◽  
Won Sub Moon ◽  
Chan Ho Lee ◽  
Ho Young You ◽  
Dong Won Jung
Keyword(s):  
Stamping Process ◽  
Forming Analysis ◽  
Auto Body ◽  
Body Panel

The Development of Forming Analysis Technology for Material Selection Based on Different Manufacturing in REF SILL OTR-R/L Auto-Body Panel Stamping

2012 ◽  
Vol 252 ◽  
pp. 438-442
Author(s):  
Dong Won Jung ◽  
Dong Hong Kim ◽  
Bong Chun Kim
Keyword(s):  
Material Selection ◽  
Implicit Method ◽  
Die Design ◽  
New Method ◽  
Good Information ◽  
Commercial Software ◽  
Stamping Process ◽  
Forming Analysis ◽  
Auto Body ◽  
Body Panel

Using a new method in this study, we were able to solve the problem with the existing method, which was panel manufacturing after selecting the most appropriate material from the possible manufacturing material. The possibility of application in the practical industry site and validity were verified. This study involves analyzing the stamping process problems by using AutoForm commercial software, which used the static-implicit method. According to this study, the results of the simulation will provide engineers good information to access the die design for optimization.

Metal Forming Analysis

2001 ◽  
Author(s):  
R. H. Wagoner ◽  
J.-L. Chenot
Keyword(s):  
Metal Forming ◽  
Forming Analysis

scholarly journals A Study on the Aspheric Glass tens Forming Analysis in the Progressive GMP Process

2007 ◽  
Vol 11 (3) ◽  
pp. 85-92 ◽  
Author(s):  
Sung-Ho Chang ◽  
Young-Min Lee ◽  
Kwang-Ho Shin ◽  
Young-Moo Heo
Keyword(s):  
Forming Analysis

scholarly journals Stamping Monitoring by Using an Adaptive 1D Convolutional Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 262
Author(s):  
Chih-Yung Huang ◽  
Zaky Dzulfikri
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Template Matching ◽  
Health Condition ◽  
Vibration Measurement ◽  
One Dimensional ◽  
Stamping Process ◽  
Metalworking Industry ◽  
Increasing Demand ◽  
Wear Condition

Stamping is one of the most widely used processes in the sheet metalworking industry. Because of the increasing demand for a faster process, ensuring that the stamping process is conducted without compromising quality is crucial. The tool used in the stamping process is crucial to the efficiency of the process; therefore, effective monitoring of the tool health condition is essential for detecting stamping defects. In this study, vibration measurement was used to monitor the stamping process and tool health. A system was developed for capturing signals in the stamping process, and each stamping cycle was selected through template matching. A one-dimensional (1D) convolutional neural network (CNN) was developed to classify the tool wear condition. The results revealed that the 1D CNN architecture a yielded a high accuracy (>99%) and fast adaptability among different models.

Recyclable conductive nanoclay for direct in situ printing flexible electronics

2021 ◽  
Author(s):  
Pengcheng Wu ◽  
Zhenwei Wang ◽  
Xinhua Yao ◽  
Jianzhong Fu ◽  
Yong He
Keyword(s):  
Flexible Electronics ◽  
Self Healing ◽  
Stamping Process

A recyclable, self-healing conductive nanoclay and corresponding stamping process are developed for printing flexible electronics directly and quickly in situ.

scholarly journals Constitutive modeling of TA15 alloy sheet coupling phase transformation in non-isothermal hot stamping process

2021 ◽  
Vol 12 ◽  
pp. 629-642
Author(s):  
Yuan Chen ◽  
Shuhui Li ◽  
Yongfeng Li ◽  
Yaoqi Wang ◽  
Zhiqiang Li ◽  
...  
Keyword(s):  
Phase Transformation ◽  
Constitutive Modeling ◽  
Hot Stamping ◽  
Alloy Sheet ◽  
Coupling Phase ◽  
Stamping Process ◽  
Ta15 Alloy
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